This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxId) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The data was extracted from a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018. This dataset is used to demonstrate how to make data Findeable, Accessible, Discoverable and Interoperable(FAIR) and how Tabular Data Package representations can be easily mobilized for re-analysis and data science. It is associated to the following project available from github at: https://github.com/proccaserra/rose2018ng-notebook with all necessary information and Jupyter notebooks.

This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms.

The data was extracted from a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018. This supplementary material table was deposited to Zenodo and is identified by the following doi: https://doi.org/10.5281/zenodo.2598799

This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR) and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.

It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessary information, executable code and tutorials in the form of Jupyter notebooks.

A collection of 22 data set of 50+ requirements each, expressed as user stories.

The dataset has been created by gathering data from web sources and we are not aware of license agreements or intellectual property rights on the requirements / user stories. The curator took utmost diligence in minimizing the risks of copyright infringement by using non-recent data that is less likely to be critical, by sampling a subset of the original requirements collection, and by qualitatively analyzing the requirements. In case of copyright infringement, please contact the dataset curator (Fabiano Dalpiaz, f.dalpiaz@uu.nl) to discuss the possibility of removal of that dataset [see Zenodo's policies]

The data sets have been originally used to conduct experiments about ambiguity detection with the REVV-Light tool: https://github.com/RELabUU/revv-light

This collection has been originally published in Mendeley data: https://data.mendeley.com/datasets/7zbk8zsd8y/1

Overview of the datasets [data and links added in December 2024]

The following text provides a description of the datasets, including links to the systems and websites, when available. The datasets are organized by macro-category and then by identifier.

Public administration and transparency

g02-federalspending.txt (2018) originates from early data in the Federal Spending Transparency project, which pertain to the website that is used to share publicly the spending data for the U.S. government. The website was created because of the Digital Accountability and Transparency Act of 2014 (DATA Act). The specific dataset pertains a system called DAIMS or Data Broker, which stands for DATA Act Information Model Schema. The sample that was gathered refers to a sub-project related to allowing the government to act as a data broker, thereby providing data to third parties. The data for the Data Broker project is currently not available online, although the backend seems to be hosted in GitHub under a CC0 1.0 Universal license. Current and recent snapshots of federal spending related websites, including many more projects than the one described in the shared collection, can be found here.

g03-loudoun.txt (2018) is a set of extracted requirements from a document, by the Loudoun County Virginia, that describes the to-be user stories and use cases about a system for land management readiness assessment called Loudoun County LandMARC. The source document can be found here and it is part of the Electronic Land Management System and EPlan Review Project - RFP RFQ issued in March 2018. More information about the overall LandMARC system and services can be found here.

g04-recycling.txt(2017) concerns a web application where recycling and waste disposal facilities can be searched and located. The application operates through the visualization of a map that the user can interact with. The dataset has obtained from a GitHub website and it is at the basis of a students' project on web site design; the code is available (no license).

g05-openspending.txt (2018) is about the OpenSpending project (www), a project of the Open Knowledge foundation which aims at transparency about how local governments spend money. At the time of the collection, the data was retrieved from a Trello board that is currently unavailable. The sample focuses on publishing, importing and editing datasets, and how the data should be presented. Currently, OpenSpending is managed via a GitHub repository which contains multiple sub-projects with unknown license.

g11-nsf.txt (2018) refers to a collection of user stories referring to the NSF Site Redesign & Content Discovery project, which originates from a publicly accessible GitHub repository (GPL 2.0 license). In particular, the user stories refer to an early version of the NSF's website. The user stories can be found as closed Issues.

(Research) data and meta-data management

g08-frictionless.txt (2016) regards the Frictionless Data project, which offers an open source dataset for building data infrastructures, to be used by researchers, data scientists, and data engineers. Links to the many projects within the Frictionless Data project are on GitHub (with a mix of Unlicense and MIT license) and web. The specific set of user stories has been collected in 2016 by GitHub user @danfowler and are stored in a Trello board.

g14-datahub.txt (2013) concerns the open source project DataHub, which is currently developed via a GitHub repository (the code has Apache License 2.0). DataHub is a data discovery platform which has been developed over multiple years. The specific data set is an initial set of user stories, which we can date back to 2013 thanks to a comment therein.

g16-mis.txt (2015) is a collection of user stories that pertains a repository for researchers and archivists. The source of the dataset is a public Trello repository. Although the user stories do not have explicit links to projects, it can be inferred that the stories originate from some project related to the library of Duke University.

g17-cask.txt (2016) refers to the Cask Data Application Platform (CDAP). CDAP is an open source application platform (GitHub, under Apache License 2.0) that can be used to develop applications within the Apache Hadoop ecosystem, an open-source framework which can be used for distributed processing of large datasets. The user stories are extracted from a document that includes requirements regarding dataset management for Cask 4.0, which includes the scenarios, user stories and a design for the implementation of these user stories. The raw data is available in the following environment.

g18-neurohub.txt (2012) is concerned with the NeuroHub platform, a neuroscience data management, analysis and collaboration platform for researchers in neuroscience to collect, store, and share data with colleagues or with the research community. The user stories were collected at a time NeuroHub was still a research project sponsored by the UK Joint Information Systems Committee (JISC). For information about the research project from which the requirements were collected, see the following record.

g22-rdadmp.txt (2018) is a collection of user stories from the Research Data Alliance's working group on DMP Common Standards. Their GitHub repository contains a collection of user stories that were created by asking the community to suggest functionality that should part of a website that manages data management plans. Each user story is stored as an issue on the GitHub's page.

g23-archivesspace.txt (2012-2013) refers to ArchivesSpace: an open source, web application for managing archives information. The application is designed to support core functions in archives administration such as accessioning; description and arrangement of processed materials including analog, hybrid, and
born digital content; management of authorities and rights; and reference service. The application supports collection management through collection management records, tracking of events, and a growing number of administrative reports. ArchivesSpace is open source and its

This dataset is to be used for the Frictionless Data package testing

This dataset consists of three different carbon price development scenarios. Each is represented by two growth rates which results in a total of 6 time series. The time frame is from 2020 to 2050. The units of the values are given in € / t CO₂. All values are nominal.

Overall, it should be noted that an estimate of the development of CO2 prices in the german nEHS and EU-ETS is subject to great uncertainty due to the major influence of regulatory intervention, a less liquid market towards 2030 and a lack of markets after 2030.

The data provided is delivered in frictionless data format (see 2024-03-25_metadata_carbon-price-scenarios.package.json) and can be accessed using the frictionless software (https://frictionlessdata.io/).

The Electrification Futures Study (EFS) is a multi-year study conducted by NREL and its research partners—Electric Power Research Institute, Evolved Energy Research, Lawrence Berkeley National Laboratory, Northern Arizona University, and Oak Ridge National Laboratory. EFS used multiple analytic tools and models to develop and assess electrification scenarios designed to quantify potential energy, economic, and environmental impacts to the U.S. power system and broader economy. There are six reports comprising the EFS, with the final report released in May 2021. Archived from https://www.nrel.gov/analysis/electrification-futures.html

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

NOTE! The data has been removed from this metadata and is nowadays available via FTIA's service for data downloads: https://ava.vaylapilvi.fi/ava/Tie/Tieliikenneonnettomuudet

Finnish Transport Infrastructure Agency collects annual road trafic accident data, which are based on information received from the law enforcement officials, and completes this data with the assistance of Statistics Finland.

This material has been created with Datapackage-standard in mind. For more information, visit: http://frictionlessdata.io/data-packages/

This shared material consists of two tables in CSV-format, and includes information of the accident and involved parties in the accident.

This data does not include any records of traffic accidents that occured in Åland. The X and Y columns are in the standard Finnish ETRS-TM35FIN –format.

A road traffic accident is an accident where there is damage to property and / or personal injury caused by the movement of the vehicle due to a traffic incident. Accident involves at least one moving vehicle , or means of transportation , and has occured in a public road or known road intended for general traffic.

This is a collection of verb paradigms in Classical Tibetan (Written Tibetan), conforming to the Paralex (https://www.paralex-standard.org) standard. The metadata conforms to the Frictionless (https://frictionlessdata.io/) standard. Datafiles are encoded as csv files.

O_WESTERSCHELDE - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding in East Flanders (Belgium) is a bird tracking dataset published by the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected by the LifeWatch GPS tracking network for large birds (http://lifewatch.be/en/gps-tracking-network-large-birds) for the project/study O_WESTERSCHELDE, using trackers developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, http://www.uva-bits.nl). The study was operational from 2018 to 2020. In total 13 individuals of Eurasian oystercatchers (Haematopus ostralegus) have been tagged in their breeding area in East Flanders (Belgium), west of the river Scheldt, mainly to study their habitat use on mudflats of the Western Scheldt (the Netherlands). Data are periodically uploaded from the UvA-BiTS database to Movebank and from there archived on Zenodo (see https://github.com/inbo/bird-tracking).

Files

Data in this package are exported from Movebank study 1099562810. Fields in the data follow the Movebank Attribute Dictionary and are described in datapackage.json. Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/records/5070086/files/datapackage.json using frictionless.

• datapackage.json: technical description of the data files.
• O_WESTERSCHELDE-reference-data.csv: reference data about the animals, tags and deployments.
• O_WESTERSCHELDE-gps-yyyy.csv: GPS data recorded by the tags, grouped by year.
• O_WESTERSCHELDE-acceleration-yyyy.csv: acceleration data recorded by the tags, grouped by year.

Acknowledgements

This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch. Additional funding was provided by the Sovon Dutch Centre for Field Ornithology.

O_BALGZAND - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) wintering on Balgzand (the Netherlands) is a bird tracking dataset published by Sovon, the University of Amsterdam and the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected during CHIRP (Cumulative Human Impact on biRd Populations) for the study O_BALGZAND using trackers developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, http://www.uva-bits.nl). The study was operational from 2010 to 2014. In total 22 individuals of Eurasian oystercatchers (Haematopus ostralegus) have been tagged while overwintering in the Balgzand area in the Western Wadden Sea (the Netherlands), mainly to study how they utilize intertidal flats in relation to food availability in winter. Data are uploaded from the UvA-BiTS database to Movebank and from there archived on Zenodo (see https://github.com/inbo/bird-tracking). No new data are expected.

Files

Data in this package are exported from Movebank study 1605798640. Fields in the data follow the Movebank Attribute Dictionary and are described in datapackage.json. Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/records/5653442/files/datapackage.json using frictionless.

• datapackage.json: technical description of the data files.
• O_BALGZAND-reference-data.csv: reference data about the animals, tags and deployments.
• O_BALGZAND-gps-yyyy.csv.gz: GPS data recorded by the tags, grouped by year.
• O_BALGZAND-acceleration-yyyy.csv.gz: acceleration data recorded by the tags, grouped by year.

Acknowledgements

These data were collected by Sovon in collaboration with the University of Amsterdam (UvA). Funding was provided by the project Monitoring abundance, composition, development and spatial variation in macrozoobenthos and birds of the national programme for sea and coastal research (ZKO) of the Netherlands Organization for Scientific Research (NWO). Additional funding was provided by NAM and supported by the UvA-BiTS virtual lab on the Dutch national e-infrastructure, built with support of LifeWatch, the Netherlands eScience Center, SURFsara and SURFfoundation. The dataset was published with funding from Stichting NLBIF - Netherlands Biodiversity Information Facility.

Dados Abertos sobre Planejamento e Monitoramento. Esse conjunto de dados, documentado de acordo com o padrão de metadados Frictionless, corresponde ao modelo dimensional que alimenta a consulta Planejamento e Monitoramento do Portal da Transparência do Estado de Minas Gerais. Ele é composto pelas seguintes tabelas fato (e tabelas dimensões associadas): - ft_plan_acao_ppag - fl_plan_indicador - ft_plan_indic_referencia - ft_plan_indic_plan_exec - fl_plan_programa - fl_plan_responsavel - ft_plan_exec_of_tipoorc - ft_plan_exec_of_territorio - ft_plan_exec_of_fonte - fl_plan_acao - ft_plan_fonte_fin_acao - ft_plan_prog_fftd - ft_plan_prog_mensal - ft_plan_prog_territorial - ft_plan_execucao_acao - ft_plan_prog_of_tipoorc - ft_plan_prog_of_territorio - ft_plan_prog_of_fonte ## Como participar Saiba como contribuir com a documentação deste conjunto de dados! A documentação deste conjunto de dados está sendo feita de forma aberta e colaborativa no Github. Existem duas alternativas para enviar sua contribuição: - Issues: Para iniciar uma discussão sobre melhorias na documentação. - Pull requests: Para sugerir uma alteração concreta na documentação. Todas as contribuições são bem vindas. Alguns exemplos são: * Indicação de expressões imprecisas presentes na documentação; * Sugestões para inclusão de descrições em campos específicos; * Sugestões para clareza na organização das ideias; * Correção de erros de ortografia e gramática. Além disso, fique a vontade para utilizar os demais canais oficiais de atendimento do Poder Executivo Estadual: - Fale Conosco: Dúvidas - Manifestações de Ouvidoria: Denúncia, Reclamação, Crítica, Elogio ou Sugestões. - Pedido de Acesso à Informação: Acesso às informações dos órgãos e entidades estaduais que não estejam publicamente disponíveis. - Pedido de abertura de bases de dados: Solicitação de abertura de bases de dados dos órgãos e entidades que não estejam publicamente disponíveis. ## Controle de alterações Documentação das principais alterações sofridas por este conjunto de dados. ### [0.1.0] - 2022-06-24 - Versão inicial

HUOM! Aineistot on poistettu tältä metatiedolta ja ovat ladattavissa jatkossa Väyläviraston Aineistonvälitysalustalta täältä: https://ava.vaylapilvi.fi/ava/Tie/Tieliikenneonnettomuudet

Väylävirasto kerää vuosittain tieliikenneonnettomuuksiin liittyvää dataa poliisilta saatujen tietojen perusteella ja täydentää ne tilastokeskuksen avustuksella.

Ainesto on toteutettu Datapackage-standardin ohjeiden mukaan. Lisätietoja: http://frictionlessdata.io/data-packages/

Jaettava aineisto sisältää kaksi taulua CSV-muodossa, sisältäen tietoja onnettomuudesta ja sen osallisista. Aineistossa olevat sijaintitiedot (X- ja Y-sarakkeet) ovat ETRS-TM35FIN -koordinaatistossa.

Aineisto ei sisällä tietoja Ahvenanmaalla sattuneista onnettomuuksista.

Tieliikenneonnettomuus on omaisuusvahinkoja ja/tai henkilövahinkoja aiheuttanut kulkuneuvon liikkumisesta johtunut liikennetapahtuma, jossa on ollut osallisena ainakin yksi liikkuva ajo- taikka kulkuneuvo ja joka on tapahtunut liikenteeseen yleisesti käytetyllä alueella.

The EIA Form 176, also known as the Annual Report of Natural and Supplemental Gas Supply and Disposition, describes the origins, suppliers, and disposition of natural gas on a yearly and state by state basis. Archived from https://www.eia.gov/naturalgas/ngqs/

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

O_ASSEN - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding in Assen (the Netherlands) is a bird tracking dataset published by the Vogelwerkgroep Assen, Netherlands Institute of Ecology (NIOO-KNAW), Sovon, Radboud University, the University of Amsterdam and the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected for the study O_ASSEN using trackers developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, http://www.uva-bits.nl). The study was operational from 2018 to 2019. In total 6 individuals of Eurasian oystercatchers (Haematopus ostralegus) have been tagged as a breeding bird in the city of Assen (the Netherlands), mainly to study space use of oystercatchers breeding in urban areas. Data are uploaded from the UvA-BiTS database to Movebank and from there archived on Zenodo (see https://github.com/inbo/bird-tracking). No new data are expected.

See van der Kolk et al. (2022, https://doi.org/10.3897/zookeys.1123.90623) for a more detailed description of this dataset.

Files

Data in this package are exported from Movebank study 1605797471. Fields in the data follow the Movebank Attribute Dictionary and are described in datapackage.json. Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/records/10053903/files/datapackage.json using frictionless.

• datapackage.json: technical description of the data files.
• O_ASSEN-reference-data.csv: reference data about the animals, tags and deployments.
• O_ASSEN-gps-yyyy.csv.gz: GPS data recorded by the tags, grouped by year.
• O_ASSEN-acceleration-yyyy.csv.gz: acceleration data recorded by the tags, grouped by year.

Acknowledgements

These data were collected by Bert Dijkstra and Rinus Dillerop from Vogelwerkgroep Assen, in collaboration with the Netherlands Institute of Ecology (NIOO-KNAW), Sovon, Radboud University and the University of Amsterdam (UvA). Funding was provided by the Prins Bernard Cultuurfonds Drenthe, municipality of Assen, IJsvogelfonds (from Birdlife Netherlands and Nationale Postcodeloterij) and the Waterleiding Maatschappij Drenthe. The dataset was published with funding from Stichting NLBIF - Netherlands Biodiversity Information Facility.

Brief data description

This data consists of the raw sensor data from a tagging study on European eel (Anguilla anguilla L.) caught and released in Nieuwpoort Belgium. The applied tags were pop-off G5 data storage tags (CEFAS Technology, Lowestoft, UK). Temperature was measured every 10 seconds and pressure (i.e. depth) every 2 seconds. The sensor data contains the raw data per eel with the tag ID as an individual eel. The tags were externally attached to eels and came off before or at a preprogrammed time, drifted to the surface, washed ashore and when found, the data could be downloaded when the tag was retrieved. Note that some recovered tags were reused hence a tag ID can occur more than once.

This data is part of the eel-pdst-analysis GitHub repository: https://github.com/PieterjanVerhelst/eel-pdst-analysis. The sensor files have the following destination: eel-pdst-analysis\data\interim\sensorlogs

Files

Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/record/8398240/files/datapackage.json using frictionless.

More Info

For more information on the data collection and analysis, see the following two research papers:

Scientific Reports: https://doi.org/10.1038/s41598-021-04052-7

Science of The Total Environment: https://doi.org/10.1016/j.scitotenv.2023.167341

LBBG_ADULT - Lesser black-backed gulls (Larus fuscus, Laridae) breeding in Belgium is a bird tracking dataset published by the Research Institute for Nature and Forest (INBO). It contains animal tracking data collected by the LifeWatch GPS tracking network for large birds (http://lifewatch.be/en/gps-tracking-network-large-birds) for the project/study LBBG_ADULT, using trackers developed by Ornitela (https://www.ornitela.com). The study has been operational since 2022. In total 39 individuals of lesser black-backed gull (Larus fuscus) have been tagged in the breeding colony of Zeebrugge in Belgium, mainly to study their habitat use and migration behaviour. Data are automatically synced with Movebank and from there periodically archived on Zenodo (see https://github.com/inbo/bird-tracking).

Files

Data in this package are exported from Movebank study 2298738353. Fields in the data follow the Movebank Attribute Dictionary and are described in datapackage.json. Files are structured as a Frictionless Data Package. You can access all data in R via https://zenodo.org/records/10055494/files/datapackage.json using frictionless.

• datapackage.json: technical description of the data files.
• LBBG_ADULT-reference-data.csv: reference data about the animals, tags and deployments.
• LBBG_ADULT-gps-yyyy.csv.gz: GPS data recorded by the tags, grouped by year.

Acknowledgements

This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch.

Dados Abertos sobre os processos de compras de materiais e serviços realizados pelo Estado e os contratos firmados entre o Estado e terceiros. Esse conjunto de dados, documentado de acordo com o padrão de metadados Frictionless, corresponde ao modelo dimensional que alimenta a consulta Compras e Contratos do Portal da Transparência do Estado de Minas Gerais. Ele é composto pelas seguintes tabelas fato (e tabelas dimensões associadas): - ft_compras - ft_compras_contrato - fl_compras_empenho ## Como participar Saiba como contribuir com a documentação deste conjunto de dados! A documentação deste conjunto de dados está sendo feita de forma aberta e colaborativa no Github. Existem duas alternativas para enviar sua contribuição: - Issues: Para iniciar uma discussão sobre melhorias na documentação. - Pull requests: Para sugerir uma alteração concreta na documentação. Todas as contribuições são bem vindas. Alguns exemplos são: * Indicação de expressões imprecisas presentes na documentação; * Sugestões para inclusão de descrições em campos específicos; * Sugestões para clareza na organização das ideias; * Correção de erros de ortografia e gramática. Além disso, fique a vontade para utilizar os demais canais oficiais de atendimento do Poder Executivo Estadual: - Fale Conosco: Dúvidas - Manifestações de Ouvidoria: Denúncia, Reclamação, Crítica, Elogio ou Sugestões. - Pedido de Acesso à Informação: Acesso às informações dos órgãos e entidades estaduais que não estejam publicamente disponíveis. - Pedido de abertura de bases de dados: Solicitação de abertura de bases de dados dos órgãos e entidades que não estejam publicamente disponíveis. ## Controle de alterações Documentação das principais alterações sofridas por este conjunto de dados. ### [0.1.0] - 2021-12-29 - Versão inicial

The EIA Form 191, also known as the Monthly Underground Natural Gas Storage Report, describes the working and base gas in reservoirs, injections, withdrawals, and location of reservoirs by field monthly. Archived from https://www.eia.gov/naturalgas/ngqs/

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into "https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:

• The PUDL Repository on GitHub
• PUDL Documentation
• Other Catalyst Cooperative data archives

This dataset, in the form of a Frictionless Tabular Data Package (https://frictionlessdata.io/specs/tabular-data-package/), holds the measurements of 61 known metabolites (all annotated with resolvable CHEBI identifiers and InChi strings), measured by gas chromatography mass-spectrometry (GC-MS) in 6 different Rose cultivars (all annotated with resolvable NCBITaxonomy Identifiers) and 3 organism parts (all annotated with resolvable Plant Ontology identifiers). The quantitation types are annotated with resolvable STATO terms.

The data were extracted from:

• a supplementary material table, available from https://static-content.springer.com/esm/art%3A10.1038%2Fs41588-018-0110-3/MediaObjects/41588_2018_110_MOESM3_ESM.zip and published alongside the Nature Genetics manuscript identified by the following doi: https://doi.org/10.1038/s41588-018-0110-3, published in June 2018
• a supplementary material table available as a pdf from "Biosynthesis of monoterpene scent compounds in roses" by Magnard et al, Science 03 Jul 2015 identified by the following doi: https://doi.org/10.1126/science.aab0696

This dataset is used to demonstrate how to make data Findable, Accessible, Discoverable and Interoperable (FAIR) and how Frictionless Tabular Data Package representations can be easily mobilised for reanalysis and data science.

It is associated to the following project: https://github.com/proccaserra/rose2018ng-notebook with all the necessary information, executable code and tutorials in the form of Jupyter notebooks.

O_VLIELAND - Eurasian oystercatchers (Haematopus ostralegus, Haematopodidae) breeding and wintering on Vlieland (the Netherlands) O_VLIELAND Haematopus ostralegus Netherlands Institute of Ecology (NIOO-KNAW) Sovon Radboud University University of Amsterdam Research Institute for Nature and Forest (INBO) CHIRP http://www.uva-bits.nl https://github.com/inbo/bird-tracking See van der Kolk et al. (2022, https://doi.org/10.3897/zookeys.1123.90623 These data were collected by the Netherlands Institute of Ecology (NIOO-KNAW), in collaboration with Sovon, Radboud University and the University of Amsterdam (UvA) for the CHIRP (Cumulative Human Impact on biRd Populations) project. Funding was provided by the Applied and Engineering Sciences domain of the Netherlands Organisation for Scientific Research (NWO-TTW 14638) and co-funding via NWO-TTW by Royal Netherlands Air Force, Birdlife Netherlands, NAM gas exploration and Deltares. The dataset was published with funding from Stichting NLBIF - Netherlands Biodiversity Information Facility. Data have been standardized to Darwin Core using the movepub https://doi.org/10.5281/zenodo.10053988 1605802367